Move column by name to front of table in pandas

We can use loc to reorder by passing a list:

In [27]:
# get a list of columns
cols = list(df)
# move the column to head of list using index, pop and insert
cols.insert(0, cols.pop(cols.index('Mid')))
cols
Out[27]:
['Mid', 'Net', 'Upper', 'Lower', 'Zsore']
In [28]:
# use ix to reorder
df = df.loc[:, cols]
df
Out[28]:
                      Mid Net  Upper   Lower  Zsore
Answer_option                                      
More_than_once_a_day    2  0%  0.22%  -0.12%     65
Once_a_day              3  0%  0.32%  -0.19%     45
Several_times_a_week    4  2%  2.45%   1.10%     78
Once_a_week             6  1%  1.63%  -0.40%     65

Another method is to take a reference to the column and reinsert it at the front:

In [39]:
mid = df['Mid']
df.drop(labels=['Mid'], axis=1,inplace = True)
df.insert(0, 'Mid', mid)
df
Out[39]:
                      Mid Net  Upper   Lower  Zsore
Answer_option                                      
More_than_once_a_day    2  0%  0.22%  -0.12%     65
Once_a_day              3  0%  0.32%  -0.19%     45
Several_times_a_week    4  2%  2.45%   1.10%     78
Once_a_week             6  1%  1.63%  -0.40%     65

You can, with very early versions of Pandas, also use ix to achieve the same results:

df = df.ix[:, cols]

But ix was deprecated from pandas 0.20.0 onwards and was discontinued as of Pandas 1.0.

Maybe I'm missing something, but a lot of these answers seem overly complicated. You should be able to just set the columns within a single list:

Column to the front:

df = df[ ['Mid'] + [ col for col in df.columns if col != 'Mid' ] ]

Or if instead, you want to move it to the back:

df = df[ [ col for col in df.columns if col != 'Mid' ] + ['Mid'] ]

Or if you wanted to move more than one column:

cols_to_move = ['Mid', 'Zsore']
df           = df[ cols_to_move + [ col for col in df.columns if col not in cols_to_move ] ]